In image processing and analysis, a local feature may be a piece of information that is relevant for a particular processing or analysis task. Determining a local feature may involve two components, such as a detector and a descriptor. The detector may identify a feature for further processing and analysis. The detector may detect and select a small subset of distinctive points (e.g., a number of pixels) from a whole image. The detector may attempt to select stable image points that are informative about image content.
The descriptor may characterize content of local patches, for instance, centered at the selected points. The descriptor may describe each local patch in a distinctive way having a feature descriptor with a lower data dimension than that of the local patch itself. The overall usefulness of the feature in processing or analysis may be affected by reliability and accuracy of the detection (e.g., localization) and/or distinctiveness of the description.
Compactly representing images and accurately finding corresponding regions between images are issues in computerized image and video processing, such with image recognition and tracking, among others. Although some approaches have been successful in image recognition and tracking, for example, these approaches may be difficult to use in mobile applications. For instance, these approaches may be computationally demanding, may require a large amount of storage (e.g., memory), and/or the storage requirement also may incur additional bandwidth consumption if network transmission is utilized.